Real Time LiDAR Point Cloud Compression and Transmission for Intelligent Transportation System

Anand, Bhaskar and Barsaiyan, Vivek and Senapati, Mrinal and Rajalakshmi, P (2019) Real Time LiDAR Point Cloud Compression and Transmission for Intelligent Transportation System. In: 89th IEEE Vehicular Technology Conference, VTC Spring, 28 April -1 May 2019, Kuala Lumpur, Malaysia.

Full text not available from this repository. (Request a copy)

Abstract

Real-time data transmission is one of the challenging tasks for LiDAR (Light Detection and Ranging) based applications. These applications are becoming more popular in the field of Surveying and Intelligent Transportation System (ITS). The size of Point cloud data (pcd files) generated by LiDAR is generally quite large. In this paper, a real-time Point cloud transmission over Wi-Fi is suggested. Also in order to avoid the transmission of huge data, an Octree-based Point cloud Compression technique is used. This Compression technique is provided by Point cloud Library (PCL). We encode the Point clouds into text files of much lower size as compared to pcd file size. Instead of sending the Point cloud data we send the text files which is further decoded on the receiver side. The preliminary experimental results show that this method has the potential to be used for an exchange of information (3-D view or Point cloud) between two vehicles for Intelligent Transportation System.

[error in script]
IITH Creators:
IITH CreatorsORCiD
Rajalakshmi, PUNSPECIFIED
Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Intelligent transportation system (ITS), LiDAR, Octree based compression, Point cloud, Point cloud library (pcl)
Subjects: Electrical Engineering
Divisions: Department of Electrical Engineering
Depositing User: Team Library
Date Deposited: 29 Jul 2019 05:28
Last Modified: 29 Jul 2019 05:28
URI: http://raiith.iith.ac.in/id/eprint/5826
Publisher URL: http://doi.org/10.1109/VTCSpring.2019.8746417
Related URLs:

Actions (login required)

View Item View Item
Statistics for RAIITH ePrint 5826 Statistics for this ePrint Item